Prefeitura PA Belém: Multas

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations include idempotentHint=true and readOnlyHint=false, but the description explains the actual behavior: calling with no args returns a login link, calling with token authenticates. It also discloses that the token can be permanent if added to config, which is beyond the annotations. However, it doesn't explicitly state side effects like session creation or token validation errors, but the description is quite informative given the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately concise, with clear front-loading of context (MCP.AI for IDE agents) and practical instructions. It uses a compact yet detailed format, covering both usage paths without unnecessary fluff. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Even without an output schema, the description covers the essential aspects: how to authenticate, both permanent and session methods, and optional parameter usage. It is complete for this tool's complexity, providing all necessary information for an agent to use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has one parameter 'token' with no description coverage (0%). The description explains that the token is a JWT to be passed for session-only login, and that calling without args returns a link. This adds meaning to the parameter, but it doesn't specify format details or constraints beyond 'JWT'. Given the low schema coverage, the description compensates partially, but with only one param, a score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: to authenticate an AI agent with MCP.AI by either obtaining a login link or accepting a pasted token. It distinguishes from sibling tools like 'connect' by focusing on authentication for IDE agents, and provides specific usage scenarios (permanent config vs session-only).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit when-to-use guidance: for IDE agents needing to log in, with two distinct workflows (adding token to config for permanent connection or pasting it for session-only). It also explains when to call with or without arguments, and mentions alternative of configuring the header directly, which helps agents decide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context beyond that: it explains that it returns connection URLs and how the response varies (authenticated true vs connect_url), which is not in the annotations. It doesn't contradict annotations, though it leaves ambiguity about partial connection states.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences: the first delivers the core purpose, the second explains behavior in two key scenarios. There is no fluff or repetition; every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having no output schema, the description covers the main return values (authenticated, pending, connect_url) and their meaning. It could be more explicit about partial connection cases, but for a simple no-parameter tool, it's adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, so the schema provides full coverage (100%). The description correctly omits param details; nothing more is needed. With no params, a baseline of 4 is appropriate as the description adds no unnecessary info.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Returns connection status and URLs.' It also outlines specific conditions (all providers connected vs missing credentials) that distinguish it from siblings like authenticate, which perform actions. The verb 'Returns' is specific and the resource is clearly connection status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use this tool (to check connection status) and describes the outcome in different states. However, it doesn't explicitly name alternatives or say 'use authenticate for authentication,' so while context is clear, exclusions are not explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations provide only minimal flags (openWorldHint, destructiveness, idempotency), so the description carries the burden. It discloses that invoke runs one-off without installing ('runs the tool pontualmente, without adding the MCP to the toolkit'), that writes require workspace owner/admin, that missing credentials yield a connect link, and that empty wallet yields a checkout/top-up link requiring retry. No contradiction found; all disclosed behaviors are consistent with the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Although long, the description is a single information-dense paragraph with zero filler. Every sentence adds value: the core flow, the KEY invoke behavior, the permission requirement, the prompt library sub-section. It is front-loaded with the most reusable guidance (search→describe→invoke flow) and uses bold/colon emphasis effectively. Length is justified by 14 actions and 23 parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, 23 undocumented parameters, and 14 actions, the description carries the complete burden and delivers: it explains the end-to-end flow, each action's purpose, permission model, edge behaviors (connect link, checkout link, one-off execution), installed-vs-workspace flags, and separates the prompt library domain cleanly. It also names sibling relationships implicitly (report_bug, request_mcp) so the agent knows the boundary of this tool vs others.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema coverage, the description must compensate, and it does substantially: every action enum value (search, describe, install, invoke, subscribe, cancel, resume, report_bug, request_mcp, list_tools, search_prompts, get_prompt, publish_prompt) is given semantic meaning tied to the flow. However, many of the 23 parameters (limit, immediate, tier_slug, cancel_reason enum, prompt_targets, prompt_vars, conversation, etc.) are only implied, not individually mapped to their schema meaning. The action-level semantics are strong but not total.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It specifies the verb (search/describe/invoke/install) plus the resource (MCPs and prompt library), and it distinguishes itself from siblings like authenticate, connect, and report_bug by mapping each sub-action to its role. The core flow (search→describe→invoke) is stated unambiguously.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Extremely explicit guidance is provided: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT'; list_tools 'lists what is callable right now'; capability requests ("find an MCP that does X", "consulta um CPF") are quoted verbatim. It also explains when to fall back to request_mcp ('asks us to build a NEW MCP when nothing fits') and covers the connect/checkout retry flow.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful context: no platform credentials required, prepaid per-query pricing, and that data is non-confidential (not 'dado sigiloso'). This goes beyond annotations without contradicting them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a few sentences, front-loaded with the tool's purpose, then covers hosting, payment, data source, and LGPD. It's efficient without excessive length, though the LGPD sentence is somewhat legalistic but still relevant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low complexity (2 simple params, no output schema), the description still lacks essential details: what data is returned, any input format constraints, and implications of incorrect parameters. The business/payment context is covered, but technical completeness is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description provides no explanation of the required parameters (placa, renavam). The agent is left without guidance on what these fields represent or their format. The tool name hints at fines, but the description doesn't compensate for the complete lack of parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool queries traffic fines (multas) from official Belém PA sources. It uses 'consulta em fonte oficial' (query in official source), which is specific and distinct from sibling tools like authenticate or marketplace. However, it doesn't specify what details are returned (e.g., amount, status), so it's not a full 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions that no platform credentials are needed and that queries are prepaid, which gives context. However, it doesn't explicitly state when to use this tool versus alternatives or when not to use it. The LGPD note implies legitimate purpose but doesn't clarify exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false, so the description does not need to restate these. It adds context that sending a conversation array is helpful for reproduction, but it does not disclose what happens after submission (e.g., no confirmation or response), which is a minor gap given the annotations cover the safety profile.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the primary purpose, and includes the only crucial additional instruction (including conversation array). No wasted words or redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a simple reporting tool with 3 parameters and no output schema. The description provides the essential usage instruction (conversation for reproduction) but doesn't explain the 'context' parameter or what the tool does with the data. Given the low complexity and annotations covering safety, the description is adequate but could benefit from clarifying the context parameter's purpose.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It mentions the 'conversation' parameter by name but does not explain the 'context' parameter or the format of the conversation string. The schema itself provides basic types and defaults, but the description adds little beyond the message and conversation mention, so it partially compensates but leaves gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: reporting a bug, missing feature, or sending feedback. It uses a specific verb ('Report') and resource (bug/feedback), and mentions the conversation array for reproduction, which distinguishes it from sibling tools that are for authentication, marketplace, or version info.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use this tool (when reporting an issue or feedback) but does not provide explicit exclusions or alternatives. It doesn't mention when not to use it, nor does it reference sibling tools that might be more appropriate for other tasks, but the context is clear enough for basic use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and idempotentHint=true, providing the safety profile. The description adds no further behavioral details beyond the resource being shown, which meets the lower bar set by good annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence that directly states the tool's function without unnecessary words or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, read-only informational tool, the description fully covers what the tool returns: platform and adapter versions. No output schema is needed, and the description is sufficient for an agent to select and invoke it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are 0 parameters, and schema coverage is 100%, so the description does not need to explain parameter details. The baseline of 4 applies as no parameters exist to document.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Show') and clearly identifies the resources ('MCP platform and adapter versions'). This distinguishes the tool from siblings like 'toolkit_info' which likely covers broader information.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives such as 'toolkit_info'. The description implies a simple version check but does not state exclusions or alternative tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so safety is covered. The description adds concrete detail about the return contents (installed MCPs, status, accounts, tool counts), which is more than the annotations alone. No side effects mentioned, but that's consistent with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence, front-loaded with the action ('Returns') and the scope ('toolkit state'), then enumerates specifics. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description serves as the primary documentation of return content. It lists the key components (installed MCPs, connection status, accounts, catalog tool counts), which is sufficient for an overview tool. It doesn't mention error cases or formatting, but for a zero-parameter read-only tool, this is adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Tool takes zero parameters)Skiping with 100% schema coverage, baseline is 4. The description doesn't need to explain parameters; instead, it clarifies the output, which is the tool's entire purpose. No parameter insight is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Returns' and clearly enumerates the contents of the toolkit state, distinguishing it from siblings like show_version. It's unambiguous about the scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description states what the tool does but gives no guidance on when to call it relative to alternatives like authenticate or connect. It doesn't suggest typical use cases or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.